Policy Engines Don't Work for AI Authorization. Here's Why

The text discusses the complexities of access control in dynamic environments, using a wedding party analogy to illustrate the limitations of traditional policy engines in handling ambient context and relational data. It contrasts two approaches to access control: traditional policy engines, which use pre-compiled, stateless rules, and Relationship-Based Access Control (ReBAC), which evaluates permissions based on current relationships and context. The text highlights the challenges posed by AI agents, which require dynamic access decisions and cannot be managed effectively with static policies. It notes that AI agents, like human users, need access systems that can adapt to changing relationships and contexts in real-time. The text argues that while traditional access control methods like access control lists and policy-based systems have their place, the future of authorization—especially for AI—lies in systems like Google's Zanzibar and SpiceDB, which are designed to handle dynamic, relationship-driven authorization at scale.

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